A model of grid cell development through spatial exploration and spike time-dependent plasticity
1Center for Learning and Memory and Department of Neuroscience, The University of Texas at Austin, Austin, TX 78712, USA.
Neuron
|July 18, 2014
Summary
This study models how grid cells in the brain develop spatial maps. A new model shows synaptic plasticity can create these cells from basic inputs, enabling path integration.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Systems Neuroscience
Background:
- Grid cell network formation mechanisms remain largely unknown.
- Development of grid cell responses is gradual after eye opening.
Purpose of the Study:
- To present a biologically plausible model for grid cell network formation.
- To investigate the role of synaptic plasticity in developing spatial representations.
Main Methods:
- Simulated an initially unstructured network of spiking neurons.
- Implemented an asymmetric spike-timing-dependent plasticity rule.
- Incorporated inputs encoding animal velocity and location.
Main Results:
- Neurons developed organized recurrent architecture based on input similarity.
- The mature network converted velocity inputs into location estimates.
- Spatially periodic responses and path integration emerged from plasticity.
Conclusions:
- Synaptic plasticity can generate grid cell properties from non-spatial inputs.
- The model predicts requirements for spatial exploration and network development.
- The model offers insights into grid period setting and response maturation.
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